[pron]

Right, the problem with SMT solvers (and the SAT solvers they're based on, although the problem there is slightly better) is that they're unpredictable and highly dependent on the form in which you pose the instance, often in very unintiitive ways (they can fail on an instance that you'd think would be as easy or even easier than another they do manage).

[dhash]

SAT/SMT hardness regression has come a long way, especially if you can insert profiling information for real instances.

If this is a production model for the cloud, the engineer should have put some thought into the encoding as to express sat/unsat clearly, if possible.

In the general case, sure, to some extent one can construct an adversarial example just as with NN (random 3-sat hardness cliff). Real world formulations of problems are either nice or atrocious IME, discoverable at dev time.

[pron]

Oh, I don't mind adversarial examples. As a user of SMT solvers (for semi-automated program verification), I just find them unpredictable and frustrating. But I've never employed SMT solvers as a library in some production system, and it's good to hear that in that case the instances could be controlled well enough for the normal operation to be predictable.